U.S. patent application number 13/784211 was filed with the patent office on 2013-07-18 for system and method for estimating and providing dispatchable operating reserve energy capacity through use of active load management.
This patent application is currently assigned to Consert Inc.. The applicant listed for this patent is Consert Inc.. Invention is credited to Joseph W. Forbes, JR., Joel L. Webb.
Application Number | 20130184888 13/784211 |
Document ID | / |
Family ID | 43050334 |
Filed Date | 2013-07-18 |
United States Patent
Application |
20130184888 |
Kind Code |
A1 |
Forbes, JR.; Joseph W. ; et
al. |
July 18, 2013 |
SYSTEM AND METHOD FOR ESTIMATING AND PROVIDING DISPATCHABLE
OPERATING RESERVE ENERGY CAPACITY THROUGH USE OF ACTIVE LOAD
MANAGEMENT
Abstract
A utility employs a method for estimating available operating
reserve. Electric power consumption by at least one device serviced
by the utility is determined during at least one period of time to
produce power consumption data. The power consumption data is
stored in a repository. A determination is made that a control
event is to occur during which power is to be reduced to one or
more devices. Prior to the control event and under an assumption
that it is not to occur, power consumption behavior expected of the
device(s) is estimated for a time period during which the control
event is expected to occur based on the stored power consumption
data. Additionally, prior to the control event, projected energy
savings resulting from the control event are determined based on
the devices' estimated power consumption behavior. An amount of
available operating reserve is determined based on the projected
energy savings.
Inventors: |
Forbes, JR.; Joseph W.;
(Wake Forest, NC) ; Webb; Joel L.; (Edmond,
OK) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Consert Inc.; |
San Antonio |
TX |
US |
|
|
Assignee: |
Consert Inc.
San Antonio
TX
|
Family ID: |
43050334 |
Appl. No.: |
13/784211 |
Filed: |
March 4, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
12775979 |
May 7, 2010 |
8396606 |
|
|
13784211 |
|
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|
Current U.S.
Class: |
700/291 |
Current CPC
Class: |
H02J 3/003 20200101;
Y04S 10/50 20130101; Y04S 20/222 20130101; Y02E 40/70 20130101;
G06Q 10/00 20130101; G05B 13/02 20130101; G06Q 50/06 20130101; H02J
3/004 20200101; Y02B 70/3225 20130101; H02J 3/14 20130101 |
Class at
Publication: |
700/291 |
International
Class: |
G05B 13/02 20060101
G05B013/02 |
Claims
1. A method for estimating operating reserve of a utility servicing
one or more service points, the method comprising: determining
amounts of electric power consumed by at least one device during at
least one period of time to produce power consumption data, the at
least one device being located at the one or more service points;
storing the power consumption data in a repository; determining
that a first control event is to occur during which a supply of
electric power is to be reduced to the at least one device;
estimating, prior to commencement of the first control event and
under an assumption that the first control event is not to occur,
power consumption behavior expected of the at least one device
during a first period of time based at least on the stored power
consumption data, wherein the first control event is expected to
occur during the first period of time; determining, prior to
commencement of the first control event, projected energy savings
resulting from the first control event based at least on the
estimated power consumption behavior of the at least one device;
and determining, prior to commencement of the first control event,
an amount of available operating reserve based on the projected
energy savings.
2. The method of claim 1, further comprising: distributing the
available operating reserve subsequent to commencement of the first
control event.
3. The method of claim 2, wherein the utility utilizes at least
some renewable energy produced by a renewable energy source and
wherein the available operating reserve is distributed to provide
regulating reserve during times of under-generation by the
renewable energy source.
4. The method of claim 1, further comprising: managing distribution
of the available operating reserve subsequent to commencement of
the first control event.
5. The method of claim 1, wherein determining that a first control
event is to occur comprises: determining that a first control event
is to occur responsive to receipt of an Automatic Generation
Control command.
6. The method of claim 1, wherein determining projected energy
savings comprises: determining an intermediate projected energy
savings for each service point at which one or more devices are to
be affected by the first control event; and aggregating the
intermediate projected energy savings for a plurality of service
points to produce the projected energy savings.
7. The method of claim 1, wherein the at least one device includes
at least one environmentally-dependent device and wherein the step
of estimating power consumption behavior of the at least one device
comprises: determining at least one environmental characteristic
expected during the first period of time at a service point at
which the at least one environmentally-dependent device is located;
determining, based on stored user settings, a maximum allowable
variance of the at least one environmental characteristic in an
area at the service point monitored by the
environmentally-dependent device; and estimating, prior to
commencement of the first control event and based at least on the
stored power consumption data, the at least one environmental
characteristic and the maximum allowable variance of the at least
one environmental characteristic, an amount of power that the at
least one environmentally-dependent device would be expected to
consume during the first period of time if the first control event
was not to occur.
8. The method of claim 7, wherein determining at least one
environmental characteristic expected during the first period of
time comprises: receiving information associated with the at least
one environmental characteristic from at least one of a local
weather service, a state weather service, and a national weather
service.
9. The method of claim 7, wherein power consumption data associated
with the service point further includes at least one of a user
setting for the maximum allowable variance of the at least one
environmental characteristic at the service point and information
relating to operating environments in which the at least one
environmentally-dependent device has operated, and wherein
estimating power consumption behavior expected of the at least one
environmentally-dependent device during the first period of time
further comprises: comparing the first period of time to time
periods stored in the repository; in the event that at least one
time period stored in the repository corresponds to at least part
of the first period of time, determining whether the repository
includes power consumption data for the at least one
environmentally-dependent device during the at least one time
period; in the event that the repository includes power consumption
data for the at least one environmentally-dependent device during
the at least one time period, determining whether at least some of
the power consumption data for the at least one time period
corresponds to a user setting and an environmental characteristic
expected during the first period of time; in the event that at
least some of the power consumption data for the at least one time
period corresponds to a user setting and an environmental
characteristic expected during the first period of time, retrieving
from the repository values corresponding to amounts of power that
the at least one environmentally-dependent device would be expected
to consume during the at least one time period if the first control
event was not to occur; in the event that none of the power
consumption data for the at least one time period corresponds to a
user setting and an environmental characteristic expected during
the first period of time, changing at least one of a search value
corresponding to an expected user setting and a search value
corresponding to an expected environmental characteristic to
produce at least one of a changed user setting search value and a
changed environmental characteristic search value; and determining
whether at least some of the power consumption data for the at
least one time period corresponds to at least one of the changed
user setting search value and the changed environmental
characteristic search value; in the event that the repository does
not include power consumption data for the at least one
environmentally-dependent device during the at least one time
period, determining whether the repository includes at least some
power consumption data for the at least one
environmentally-dependent device during a time period proximate in
time to the at least one time period; and in the event that the
repository includes at least some power consumption data for the at
least one environmentally-dependent device during a time period
proximate in time to the at least one time period, retrieving from
the at least some power consumption data values corresponding to
amounts of power that the at least one environmentally-dependent
device would be expected to consume during the at least one time
period if the first control event was not to occur.
10. The method of claim 7, wherein the at least one environmental
characteristic is at least one of air temperature, humidity,
barometric pressure, wind speed, rainfall amount, and water
temperature.
11. The method of claim 1, wherein the at least one device includes
at least one environmentally-independent device and wherein
estimating power consumption behavior expected of the at least one
device during the first period of time comprises: determining
whether, absent occurrence of the first control event, the at least
one environmentally-independent device is expected to be consuming
power during the first period of time period based on the stored
power consumption data; in the event that, absent occurrence of the
first control event, the at least one environmentally-independent
device would be consuming power during the first period of time,
determining a duty cycle for the at least one
environmentally-independent device based on the stored power
consumption data; and estimating, based on the stored power
consumption data and the duty cycle, an amount of power that the at
least one environmentally-independent device would be expected to
consume during the first period of time if the first control event
was not to occur.
12. The method of claim 1, wherein estimating power consumption
behavior of the at least one device comprises: comparing the first
period of time to time periods stored in the repository; in the
event that the first period of time corresponds to at least one
particular time period stored in the repository, determining
whether the repository includes power consumption data for the at
least one device during the at least one particular time period;
and in the event that the repository includes power consumption
data for the at least one device during the at least one particular
time period, retrieving from the repository one or more values
corresponding to one or more amounts of power that the at least one
device would be expected to consume during the first period of time
if the first control event was not to occur.
13. The method of claim 12, further comprising: in the event that
the repository does not include power consumption data for the at
least one device during the at least one particular time period,
determining whether the repository includes power consumption data
for the at least one device during time periods before and after
the at least one particular time period; and interpolating, based
on the power consumption data for the at least one device during
the time periods before and after the at least one particular time
period, one or more values corresponding to one or more amounts of
power that the at least one device would be expected to consume
during the at least one particular time period if the first control
event was not to occur.
14. The method of claim 12, further comprising: in the event that
the first period of time does not correspond to at least one time
period stored in the repository, determining whether the repository
includes power consumption data for the at least one device during
time periods before and after the first period of time; and
interpolating, based on the power consumption data for the at least
one device during the time periods before and after the first
period of time, one or more values corresponding to one or more
amounts of power that the at least one device would be expected to
consume during the first period of time if the first control event
was not to occur.
15. The method of claim 1, wherein the step of storing the power
consumption data in a repository comprises: storing the power
consumption data in a repository remote from the one or more
service points.
16. The method of claim 1, wherein determining projected energy
savings resulting from the first control event comprises:
determining an amount of power expected to be consumed by the at
least one device during the first period of time absent occurrence
of the first control event to produce first energy savings;
determining an amount of power that is not expected to be
dissipated in transmission lines as a result of not delivering
power to the at least one device during the first control event to
produce second energy savings; and summing the first energy savings
and the second energy savings.
17. The method of claim 1, wherein the step of determining
projected energy savings is performed on a service point by service
point basis.
18. The method of claim 1, wherein the step of determining
projected energy savings is performed on a utility-wide basis.
19. The method of claim 1, further comprising: initiating the first
control event; determining that a first set of one or more devices
is to be released from the first control event prior to termination
of the first control event; and determining a second set of one or
more devices to replace the first set of devices, wherein projected
energy savings from the second set of devices is greater than or
equal to an energy savings from the first set of devices.
20. A method for a first utility to acquire operating reserve from
a second utility, the method comprising: requesting operating
reserve from the second utility sufficiently in advance of a
transfer time at which the operating reserve will be needed so as
to facilitate measurable and verifiable load-controlled generation
of the operating reserve, wherein load-controlled generation of the
operating reserve results from: remote measurement of power
consumed by at least one device during at least one period of time
prior to the request for operating reserve to produce power
consumption data, the at least one device being located at one or
more service points serviced by the second utility; storage of the
power consumption data in a repository; determination that a
control event is to commence at the transfer time, wherein a supply
of electric power is to be reduced to the at least one device
during the control event; estimation, prior to commencement of the
control event and under an assumption that the control event is not
to occur, of power consumption behavior expected of the at least
one device during a time period after the transfer time based at
least on the stored power consumption data; determination, prior to
commencement of the control event, of projected energy savings
resulting from the control event based at least on the estimated
power consumption behavior of the at least one device; and
determination, prior to commencement of the control event, of an
amount of the operating reserve based on the projected energy
savings; receiving an acknowledgment from the second utility
indicating that the second utility will supply the operating
reserve at the transfer time; and receiving at least some of the
operating reserve from the second utility at the transfer time and
for a period of time thereafter.
21. The method of claim 20, wherein requesting operating reserve
from the second utility sufficiently in advance of a transfer time
at which the operating reserve will be needed comprises:
communicating an Automatic Generation Control command to the second
utility.
22. A system for implementing a virtual utility that is operable to
at least offer energy to one or more requesting utilities for use
as operating reserve for the requesting utilities, the system
comprising: a repository; and at least one processor coupled to the
repository, the at least one processor operable to: determine
amounts of electric power consumed by at least one device during at
least one period of time to produce power consumption data, the at
least one device being located remotely from the processor; store
the power consumption data in the repository; determine that a
control event is to occur during which a supply of electric power
is to be reduced to the at least one device; estimate, prior to
commencement of the control event and under an assumption that the
control event is not to occur, power consumption behavior expected
of the at least one device during a first period of time based at
least on the stored power consumption data, wherein the control
event is expected to occur during the first period of time;
determine, prior to commencement of the control event, projected
energy savings resulting from the control event based at least on
the estimated power consumption behavior of the at least one
device; determine, prior to commencement of the control event, an
amount of operating reserve based on the projected energy savings;
and manage distribution of the amount of operating reserve to at
least one of the requesting utilities subsequent to commencement of
the control event.
23. The system of claim 22, wherein the at least one processor is
further operable to determine that the control event is to occur
responsive to receipt of an Automatic Generation Control command.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a division of U.S. application Ser. No.
12/775,979, filed on May 7, 2010, which application is incorporated
herein by this reference as if fully set forth herein. Application
Ser. No. 12/775,979 is a continuation-in-part of U.S. application
Ser. No. 11/895,909 filed on Aug. 28, 2007, now U.S. Pat. No.
7,715,951, which application is incorporated herein by this
reference as if fully set forth herein. Application Ser. No.
12/775,979 is also a continuation-in-part of co-pending U.S.
application Ser. No. 12/001,819 filed on Dec. 13, 2007, which
application is incorporated herein by this reference as if fully
set forth herein. Finally, application Ser. No. 12/775,979 further
claims priority under 35 U.S.C. .sctn.119(e) upon U.S. Provisional
Application Ser. No. 61/215,725 filed on May 8, 2009 solely to the
extent of the subject matter disclosed in said provisional
application, which application is incorporated herein by this
reference as if fully set forth herein.
BACKGROUND OF THE INVENTION
[0002] 1. Field of the Invention
[0003] The present invention relates generally to the field of
electric power supply and generation systems and, more
particularly, to a system and method for estimating and/or
providing dispatchable operating reserve energy capacity for an
electric utility using active load management so that the reserve
capacity may be made available to the utility or to the general
power market (e.g., via a national grid).
[0004] 2. Description of Related Art
[0005] Energy demand within a utility's service area varies
constantly. Such variation in demand can cause undesired
fluctuations in line frequency if not timely met. To meet the
varying demand, a utility must adjust its supply or capacity (e.g.,
increase capacity when demand increases and decrease supply when
demand decreases). However, because power cannot be economically
stored, a utility must regularly either bring new capacity on-line
or take existing capacity off-line in an effort to meet demand and
maintain frequency. Bringing new capacity online involves using a
utility's reserve power, typically called "operating reserve." A
table illustrating a utility's typical energy capacity is shown in
FIG. 1. As shown, operating reserve typically includes three types
of power: so-called "regulating reserve," "spinning reserve," and
"non-spinning reserve" or "supplemental reserve." The various types
of operating reserve are discussed in more detail below.
[0006] Normal fluctuations in demand, which do not typically affect
line frequency, are responded to or accommodated through certain
activities, such as by increasing or decreasing an existing
generator's output or by adding new generating capacity. Such
accommodation is generally referred to as "economic dispatch." A
type of power referred to as "contingency reserve" is additional
generating capacity that is available for use as economic dispatch
to meet changing (increasing) demand. Contingency reserve consists
of two of the types of operating reserve, namely, spinning reserve
and non-spinning reserve. Therefore, operating reserve generally
consists of regulating reserve and contingency reserve.
[0007] As shown in FIG. 1, spinning reserve is additional
generating capacity that is already online (e.g., connected to the
power system) and, thus, is immediately available or is available
within a short period of time after a determined need (e.g., within
ten (10) to fifteen (15) minutes, as defined by the applicable
North American Electric Reliability Corporation (NERC) regulation).
More particularly, in order for contingency reserve to be
classified as "spinning reserve," the reserve power capacity must
meet the following criteria: [0008] a) be connected to the grid;
[0009] b) be measurable and verifiable; and [0010] c) be capable of
fully responding to load typically within 10-15 minutes of being
dispatched by a utility, where the time-to-dispatch requirements of
the spinning reserve are generally governed by a grid system
operator or other regulatory body, such as NERC.
[0011] Non-spinning reserve (also called supplemental reserve) is
additional generating capacity that is not online, but is required
to respond within the same time period as spinning reserve.
Typically, when additional power is needed for use as economic
dispatch, a power utility will make use of its spinning reserve
before using its non-spinning reserve because (a) the generation
methods used to produce spinning reserve capacity typically tends
to be cheaper than the methods, such as one-way traditional demand
response, used to produce non-spinning reserve or (b) the consumer
impact to produce non-spinning reserve is generally less desirable
than the options used to produce spinning reserve due to other
considerations, such as environmental concerns. For example,
spinning reserve may be produced by increasing the torque of rotors
for turbines that are already connected to the utility's power grid
or by using fuel cells connected to the utility's power grid;
whereas, non-spinning reserve may be produced from simply turning
off resistive and inductive loads such as heating/cooling systems
attached to consumer locations. However, making use of either
spinning reserve or non-spinning reserve results in additional
costs to the utility because of the costs of fuel, incentives paid
to consumers for traditional demand response, maintenance, and so
forth.
[0012] If demand changes so abruptly and quantifiably as to cause a
substantial fluctuation in line frequency within the utility's
electric grid, the utility must respond to and correct for the
change in line frequency. To do so, utilities typically employ an
Automatic Generation Control (AGC) process or subsystem to control
the utility's regulating reserve. To determine whether a
substantial change in demand has occurred, each utility monitors
its Area Control Error (ACE). A utility's ACE is equal to the
difference in the scheduled and actual power flows in the utility
grid's tie lines plus the difference in the actual and scheduled
frequency of the supplied power multiplied by a constant determined
from the utility's frequency bias setting. Thus, ACE can be written
generally as follows:
ACE=(NI.sub.A-NI.sub.S)+(-10B.sub.1)(F.sub.A-F.sub.S), [Equation
1]
[0013] where NI.sub.A is the sum of actual power flows on all tie
lines, [0014] NI.sub.S is the sum of scheduled flows on all tie
lines, [0015] B.sub.1 is the frequency bias setting for the
utility, [0016] F.sub.A is the actual line frequency, and [0017]
F.sub.S is the scheduled line frequency (typically 60 Hz).
[0018] In view of the foregoing ACE equation, the amount of loading
relative to capacity on the tie lines causes the quantity
(NI.sub.A-NI.sub.S) to be either positive or negative. When demand
is greater than supply or capacity (i.e., the utility is
under-generating or under-supplying), the quantity
(NI.sub.A-NI.sub.B) is negative, which typically causes ACE to be
negative. On the other hand, when demand is less than supply, the
quantity (NI.sub.A-NI.sub.S) is positive (i.e., the utility is
over-generating or over-supplying), which typically causes ACE to
be positive. The amount of demand (e.g., load) or capacity directly
affects the quantity (NI.sub.A-NI.sub.S); thus, ACE is a measure of
generation capacity relative to load. Typically, a utility attempts
to maintain its ACE very close zero using AGC processes.
[0019] If ACE is not maintained close to zero, line frequency can
change and cause problems for power consuming devices attached to
the electric utility's grid. Ideally, the total amount of power
supplied to the utility tie lines must equal the total amount of
power consumed through loads (power consuming devices) and
transmission line losses at any instant of time. However, in actual
power system operations, the total mechanical power supplied by the
utility's generators is seldom exactly equal to the total electric
power consumed by the loads plus the transmission line losses. When
the power supplied and power consumed are not equal, the system
either accelerates (e.g., if there is too much power in to the
generators) causing the generators to spin faster and hence to
increase the line frequency or decelerates (e.g., if there is not
enough power into the generators) causing the line frequency to
decrease. Thus, variation in line frequency can occur due to excess
supply, as well as due to excess demand.
[0020] To respond to fluctuations in line frequency using AGC, a
utility typically utilizes "regulating reserve," which is one type
of operating reserve as illustrated in FIG. 1. Regulating reserve
is used as needed to maintain constant line frequency. Therefore,
regulating reserve must be available almost immediately when needed
(e.g., in as little as a few seconds to less than about five (5)
minutes). Governors are typically incorporated into a utility's
generation system to respond to minute-by-minute changes in load by
increasing or decreasing the output of individual generators and,
thereby, engaging or disengaging, as applicable, the utility's
regulating reserve.
[0021] The Federal Energy Reliability Commission (FERC) and NERC
have proposed the concept of Demand Side Management (DSM) as an
additional approach to account for changes in demand. DSM is a
method in which a power utility carries out actions to reduce
demand during peak periods. Examples of DSM include encouraging
energy conservation, modifying prices during peak periods, direct
load control, and others.
[0022] Current approaches for using DSM to respond to increases in
demand have included using one way load switches that interrupt
loads, as well as statistics to approximate the average amount of
projected load removed by DSM. A statistical approach is employed
because of the utility's inability to measure the actual load
removed from the grid as a result of a DSM load control event. In
addition, current DSM approaches have been limited to use of a
single power measuring meter among every one hundred (100) or more
service points (e.g., residences and/or businesses). Accordingly,
current DSM approaches are inadequate because they rely on
statistical trends and sampling, rather than on empirical data, to
make projections and measure actual load removal events.
[0023] More recently, FERC and NERC have introduced the concept of
flexible load-shape programs as a component of DSM. These programs
allow customers to make their preferences known to the utility
concerning timing and reliability of DSM load control events.
However, DSM approaches utilizing load-shaping programs do not meet
all of the criteria for implementing regulating reserve or spinning
reserve, such as being dispatchable within 15 minutes or less.
Additionally, in order for a generating source to be considered
dispatchable energy, it must be forecasted twenty-four (24) hours
prior to being delivered to a utility. Current DSM approaches do
not facilitate accurate forecasting twenty-four (24) hours in
advance due to their heavy reliance on statistics.
[0024] Therefore, there is a need for utilities to be able to
create operating reserve, especially regulating and/or spinning
reserve, by using accurate forecasting and flexible load shaping
techniques. There is a further need to involve the consumer in a
two-way approach in which the consumer can make their energy
consumption preferences known and the utility can make use of those
preferences to respond to increased demand and maintain line
frequency regulation.
BRIEF DESCRIPTION OF THE DRAWINGS
[0025] FIG. 1 is a table showing the base load power requirements
and operating reserve available to an electric power utility.
[0026] FIG. 2 is a block diagram illustrating how an active load
management system in accordance with the present invention provides
additional operating (e.g., regulating, spinning and/or
non-spinning) reserve to a power utility.
[0027] FIG. 3 is a block diagram of an exemplary IP-based, active
load management system in accordance with one embodiment of the
present invention.
[0028] FIG. 4 is a block diagram illustrating an exemplary active
load director as shown in the power load management system of FIG.
3.
[0029] FIG. 5 is a block diagram illustrating generation of an
exemplary sampling repository at the active load director of FIG. 4
or some other location in an electric utility.
[0030] FIG. 6 is a screen shot of an exemplary web browser
interface through which a customer may designate his or her device
performance and energy saving preferences for an
environmentally-dependent, power consuming device in accordance
with one embodiment of the present invention.
[0031] FIG. 7 is a screen shot of an exemplary web browser
interface through which a customer may designate his or her device
performance and energy saving preferences for an
environmentally-independent, power consuming device in accordance
with another embodiment of the present invention.
[0032] FIG. 8 is an operational flow diagram illustrating a method
for empirically analyzing power usage of power consuming devices
and populating a repository with data samples resulting from such
power usage analysis, in accordance with an exemplary embodiment of
the present invention.
[0033] FIG. 9 is an operational flow diagram illustrating a method
for projecting energy usage for a power consuming device in
accordance with an exemplary embodiment of the present
invention.
[0034] FIG. 10 is an operational flow diagram illustrating a method
for estimating power consumption behavior of a power consuming
device in accordance with an exemplary embodiment of the present
invention.
[0035] FIG. 11 is an operational flow diagram illustrating a method
for projecting energy savings through power interruption to a power
consuming device during a control event, in accordance with an
exemplary embodiment of the present invention.
[0036] FIG. 12 is a graph that depicts a load profile of a utility
during a projected time period, showing actual energy usage as well
as projected energy usage determined with and without a control
event, in accordance with an exemplary embodiment of the present
invention.
[0037] FIG. 13 is a block diagram of a system for implementing a
virtual electric utility in accordance with an exemplary embodiment
of the present invention.
DETAILED DESCRIPTION
[0038] Before describing in detail exemplary embodiments that are
in accordance with the present invention, it should be observed
that the embodiments reside primarily in combinations of apparatus
components and processing steps related to actively monitoring and
managing power loading at an individual service point (e.g., on an
individual subscriber basis) and throughout a utility's service
area, as well as determining available or dispatchable operating
reserve power derived from projected power savings resulting from
monitoring and management of power loading. Accordingly, the
apparatus and method components have been represented where
appropriate by conventional symbols in the drawings, showing only
those specific details that are pertinent to understanding the
embodiments of the present invention so as not to obscure the
disclosure with details that will be readily apparent to those of
ordinary skill in the art having the benefit of the description
herein.
[0039] In this document, relational terms, such as "first" and
"second," "top" and "bottom," and the like, may be used solely to
distinguish one entity or element from another entity or element
without necessarily requiring or implying any physical or logical
relationship or order between such entities or elements. The terms
"comprises," "comprising," and any other variation thereof are
intended to cover a non-exclusive inclusion, such that a process,
method, article, or apparatus that comprises a list of elements
does not include only those elements, but may include other
elements not expressly listed or inherent to such process, method,
article, or apparatus. The term "plurality of" as used in
connection with any object or action means two or more of such
object or action. A claim element proceeded by the article "a" or
"an" does not, without more constraints, preclude the existence of
additional identical elements in the process, method, article, or
apparatus that includes the element.
[0040] Additionally, the term "ZigBee" refers to any wireless
communication protocol adopted by the Institute of Electronics
& Electrical Engineers (IEEE) according to standard 802.15.4 or
any successor standard(s), and the term "Bluetooth" refers to any
short-range communication protocol implementing IEEE standard
802.15.1 or any successor standard(s). The term "High Speed Packet
Data Access (HSPA)" refers to any communication protocol adopted by
the International Telecommunication Union (ITU) or another mobile
telecommunications standards body referring to the evolution of the
Global System for Mobile Communications (GSM) standard beyond its
third generation Universal Mobile Telecommunications System (UMTS)
protocols. The term "Long Term Evolution (LTE)" refers to any
communication protocol adopted by the ITU or another mobile
telecommunications standards body referring to the evolution of
GSM-based networks to voice, video and data standards anticipated
to be replacement protocols for HSPA. The term "Code Division
Multiple Access (CDMA) Evolution Date-Optimized (EVDO) Revision A
(CDMA EVDO Rev. A)" refers to the communication protocol adopted by
the ITU under standard number TIA-856 Rev. A.
[0041] The terms "utility," "electric utility," "power utility,"
and "electric power utility" refer to any entity that generates
and/or distributes electrical power to its customers, that
purchases power from a power-generating entity and distributes the
purchased power to its customers, or that supplies electricity
created either actually or virtually by alternative energy sources,
such as solar power, wind power, load control, or otherwise, to
power generation or distribution entities through the FERC
electrical grid or otherwise. The terms "energy" and "power" are
used interchangeably herein. The terms "operating reserve,"
"spinning reserve," "regulating reserve," "non-spinning reserve,"
"supplemental reserve," and "contingency reserve" are conventional
in the art and their uses and inter-relations are described in
Paragraphs [0005]-[0008] and [0012] above. The term "environment"
refers to general conditions, such as air temperature, humidity,
barometric pressure, wind speed, rainfall quantity, water
temperature, etc., at or proximate a service point or associated
with a device (e.g., water temperature of water in a hot water
heater or a swimming pool). The term "device," as used herein,
means a power-consuming device, and there may generally be two
different types of devices within a service point, namely, an
environmentally-dependent device and an environmentally-independent
device. An environmentally-dependent device is any power consuming
device that turns on or off, or modifies its behavior, based on one
or more sensors that detect characteristics, such as temperature,
humidity, pressure, or various other characteristics, of an
environment. An environmentally-dependent device may directly
affect and/or be affected by the environment in which it operates.
An environmentally-independent device is any power-consuming device
that turns on or off, or modifies its behavior, without reliance
upon inputs from any environmental sensors. Generally speaking, an
environmentally-independent device does not directly affect, and is
not typically affected by, the environment in which it operates,
although, as one skilled in the art will readily recognize and
appreciate, operation of an environmentally-independent device can
indirectly affect, or occasionally be affected by, the environment.
For example, as those skilled in the art readily understand, a
refrigerator or other appliance generates heat during operation,
thereby causing some heating of the ambient air proximate the
device.
[0042] It will be appreciated that embodiments or components of the
systems described herein may be comprised of one or more
conventional processors and unique stored program instructions that
control the one or more processors to implement, in conjunction
with certain non-processor circuits, some, most, or all of the
functions for determining an electric utility's available or
dispatchable operating (e.g., regulating and spinning) reserve that
is derived from projected power savings resulting from monitoring
and management of loads in one or more active load management
systems as described herein. The non-processor circuits may
include, but are not limited to, radio receivers, radio
transmitters, antennas, modems, signal drivers, clock circuits,
power source circuits, relays, meters, memory, smart breakers,
current sensors, and user input devices. As such, these functions
may be interpreted as steps of a method to store and distribute
information and control signals between devices in a power load
management system. Alternatively, some or all functions could be
implemented by a state machine that has no stored program
instructions, or in one or more application specific integrated
circuits (ASICs), in which each function or some combinations of
functions are implemented as custom logic. Of course, a combination
of the foregoing approaches could be used. Thus, methods and means
for these functions have been described herein. Further, it is
expected that one of ordinary skill in the art, notwithstanding
possibly significant effort and many design choices motivated by,
for example, available time, current technology, and economic
considerations, when guided by the concepts and principles
disclosed herein, will be readily capable of generating such
software instructions, programs and integrated circuits (ICs), and
appropriately arranging and functionally integrating such
non-processor circuits, without undue experimentation.
[0043] Generally, the present invention encompasses a system and
method for estimating operating reserve (e.g., spinning and/or
regulating reserve) for a utility servicing one or more service
points. In one embodiment, the utility employs an active load
management system (ALMS) to remotely determine, during at least one
period of time, power consumed by at least one device located at
the one or more service points and receiving power from the utility
to produce power consumption data. The power consumption data is
regularly stored and updated in a repository. The ALMS or a control
component thereof, such as an active load director (ALD),
determines an expected, future time period for a control event
during which power is to be interrupted or reduced to one or more
devices. Prior to commencement of the control event, the ALMS or
its control component: (i) estimates power consumption behavior
expected of the device(s) during the time period of the control
event based at least on the stored power consumption data, (ii)
determines projected energy savings resulting from the control
event based at least on the estimated power consumption behavior of
device(s), and determines operating (e.g., regulating and/or
spinning) reserve based on the projected energy savings. The
determined operating reserve may be made available to the current
power utility or to the power market through the existing (e.g.,
Federal Energy Regulatory Commission) power grid. In one
embodiment, the ALD populates an internal repository (e.g.,
database, matrix, or other storage medium) with measurement data
indicating how individual devices within individual service points
consume power or otherwise behave under normal operation and during
control events. The power consumption data is updated through
regular (e.g., periodic or otherwise) sampling of device operating
conditions (e.g., current draw, duty cycle, operating voltage,
etc.). When an ALD is first installed in an ALMS for an electric
utility power grid, there is little data with which to create
regulating and spinning reserve forecasts. However, over time, more
and more data samples are used to improve the quality of the data
in the repository. This repository is used to project both energy
usage and energy savings. These projections can be aggregated for
an entire service point, a group of service points, or the entire
utility.
[0044] In an alternative embodiment, additional data may be used to
help differentiate each data sample stored in the repository. The
additional data is associated with variability factors, such as,
for example, outside air temperature, day of the week, time of day,
humidity, sunlight, wind speed, altitude, orientation of windows or
doors, barometric pressure, energy efficiency rating of the service
point, insulation used at the service point, and others. All of
these variability factors can have an influence on the power
consumption of a device. Some of the variability factor data may be
obtained from public sources, such as local, state or national
weather services, calendars, and published specifications. Other
variability factor data may be obtained privately from user input
and from sensors, such as humidity, altitude, temperature (e.g., a
thermostat), and optical or light sensors, installed at or near a
service point (e.g., within or at a residence or business).
[0045] FIG. 2 is a block diagram illustrating how an ALMS operating
in accordance with the present invention provides additional
operating (e.g., regulating, spinning, and/or non-spinning) reserve
to a power utility. Without use of an ALMS operating in accordance
with the present invention, the utility has capacity equal to its
base load plus its regulating reserve, spinning reserve, and
non-spinning reserve as shown on the left side of the figure.
However, with use of an ALMS operating in accordance with the
present invention, the utility has additional operating reserve,
which may be preferably used as regulating, spinning and/or
non-spinning reserve (as illustrated in FIG. 2), by drawing power
selectively from service points through the interruption or
reduction of power to devices, such as air conditioners, furnaces,
hot water heaters, pool pumps, washers, dryers, boilers, and/or any
other inductive or resistive loads, at the service points.
[0046] The present invention can be more readily understood with
reference to FIGS. 3-12, in which like reference numerals designate
like items. FIG. 3 depicts an exemplary IP-based active load
management system (ALMS) 10 that may be utilized by an electric
utility, which may be a conventional power-generating utility or a
virtual utility, in accordance with the present invention. The
below description of the ALMS 10 is limited to specific disclosure
relating to embodiments of the present invention. A more general
and detailed description of the ALMS 10 is provided in
commonly-owned, co-pending U.S. application Ser. No. 11/895,909,
which was filed on Aug. 28, 2007, was published as U.S. Patent
Application Publication No. US 2009/0062970 A1 on Mar. 5, 2009, and
is incorporated herein by this reference as if fully set forth
herein. U.S. Patent Application Publication No. US 2009/0062970 A1
provides details with respect to the exemplary operational
implementation and execution of control events to interrupt or
reduce power to devices located at service points, such as
residences and businesses. The use of an ALMS 10 to implement a
virtual utility is described in detail in commonly-owned and
co-pending U.S. application Ser. No. 12/001,819, which was filed on
Dec. 13, 2007, was published as U.S. Patent Application Publication
No. US 2009/0063228 A1 on Mar. 5, 2009, and is incorporated herein
by this reference as if fully set forth herein.
[0047] The ALMS 10 monitors and manages power distribution via an
active load director (ALD) 100 connected between one or more
utility control centers (UCCs) 200 (one shown) and one or more
active load clients (ALCs) 300 (one shown) installed at one or more
service points 20 (one exemplary residential service point shown).
The ALD 100 may communicate with the utility control center 200 and
each active load client 300 either directly or through a network 80
using the Internet Protocol (IP) or any other (IP or Ethernet)
connection-based protocols. For example, the ALD 100 may
communicate using RF systems operating via one or more base
stations 90 (one shown) using one or more wireless communication
protocols, such as GSM, ANSI C12.22, Enhanced Data GSM Environment
(EDGE), HSPA, LTE, Time Division Multiple Access (TDMA), or CDMA
data standards, including CDMA 2000, CDMA Revision A, CDMA Revision
B, and CDMA EVDO Rev. A. Alternatively, or additionally, the ALD
100 may communicate via a digital subscriber line (DSL) capable
connection, cable television based IP capable connection, or any
combination thereof. In the exemplary embodiment shown in FIG. 3,
the ALD 100 communicates with one or more active load clients 300
using a combination of traditional IP-based communication (e.g.,
over a trunked line) to a base station 90 and a wireless channel
implementing the HSPA or EVDO protocol from the base station 90 to
the active load client 300. The distance between the base station
90 and the service point 20 or the active load client 300 is
typically referred to as the "last mile" even though the distance
may not actually be a mile. The ALD 100 may be implemented in
various ways, including, but not limited to, as an individual
server, as a blade within a server, in a distributed computing
environment, or in other combinations of hardware and software. In
the following disclosure, the ALD 100 will be described as embodied
in an individual server to facilitate an understanding of the
present invention. Thus, the server embodiment of the ALD 100
described below corresponds generally to the description of the ALD
100 in US Patent Application Publication Nos. US 2009/0062970 A1
and US 2009/0063228 A1.
[0048] Each active load client 300 is preferably accessible through
a specified address (e.g., IP address) and controls and monitors
the state of individual smart breaker modules or intelligent
appliances 60 installed at the service point 20 (e.g., in the
business or residence) to which the active load client 300 is
associated (e.g., connected or supporting). Each active load client
300 is preferably associated with a single residential or
commercial customer. In one embodiment, the active load client 300
communicates with a residential load center 400 that contains smart
breaker modules, which are able to switch from an "ON" (active)
state to an "OFF" (inactive) state, and vice versa, responsive to
signaling from the active load client 300. Smart breaker modules
may include, for example, smart breaker panels manufactured by
Schneider Electric SA under the trademark "Square D" or Eaton
Corporation under the trademark "Cutler-Hammer" for installation
during new construction. For retro-fitting existing buildings,
smart breakers having means for individual identification and
control may be used. Typically, each smart breaker controls a
single appliance (e.g., a washer/dryer 30, a hot water heater 40,
an HVAC unit 50, or a pool pump 70). In an alternative embodiment,
IP addressable relays or device controllers that operate in a
manner similar to a "smart breaker" may be used in place of smart
breakers, but would be installed coincident with the load under
control and would measure the startup power, steady state power,
power quality, duty cycle and energy load profile of the individual
appliance 60, HVAC unit 40, pool pump 70, hot water heater 40, or
any other controllable load as determined by the utility or end
customer.
[0049] Additionally, the active load client 300 may control
individual smart appliances directly (e.g., without communicating
with the residential load center 400) via one or more of a variety
of known communication protocols (e.g., IP, Broadband over
PowerLine (BPL) in its various forms, including through
specifications promulgated or being developed by the HOMEPLUG
Powerline Alliance and the Institute of Electrical and Electronic
Engineers (IEEE), Ethernet, Bluetooth, ZigBee, Wi-Fi (IEEE 802.11
protocols), HSPA, EVDO, etc.). Typically, a smart appliance 60
includes a power control module (not shown) having communication
abilities. The power control module is installed in-line with the
power supply to the appliance, between the actual appliance and the
power source (e.g., the power control module is plugged into a
power outlet at the home or business and the power cord for the
appliance is plugged into the power control module). Thus, when the
power control module receives a command to turn off the appliance
60, it disconnects the actual power supplying the appliance 60.
Alternatively, the smart appliance 60 may include a power control
module integrated directly into the appliance, which may receive
commands and control the operation of the appliance directly (e.g.,
a smart thermostat may perform such functions as raising or
lowering the set temperature, switching an HVAC unit on or off, or
switching a fan on or off).
[0050] The active load client 300 may further be coupled to one or
more variability factor sensors 94. Such sensors 94 may be used to
monitor a variety of variability factors affecting operation of the
devices, such as inside and/or outside temperature, inside and/or
outside humidity, time of day, pollen count, amount of rainfall,
wind speed, and other factors or parameters.
[0051] Referring now to FIG. 4, the ALD 100 may serve as the
primary interface to customers, as well as to service personnel,
and operates as the system controller sending control messages to,
and collecting data from, installed active load clients 300 as
described in detail below and in U.S. Patent Application
Publication No. US 2009/0062970 A1. In the exemplary embodiment
depicted in FIG. 4, the ALD 100 is implemented as an individual
server and includes a utility control center (UCC) security
interface 102, a UCC command processor 104, a master event manager
106, an ALC manager 108, an ALC security interface 110, an ALC
interface 112, a web browser interface 114, a customer sign-up
application 116, customer personal settings 138, a customer reports
application 118, a power savings application 120, an ALC diagnostic
manager 122, an ALD database 124, a service dispatch manager 126, a
trouble ticket generator 128, a call center manager 130, a carbon
savings application 132, a utility power and carbon (P&C)
database 134, a read meter application 136, a security device
manager 140, a device controller 144, and one or more processors
160 (one shown). The operational details of several of the elements
of the ALD 100 are described below with respect to their use in
connection with the present invention. The operational details of
the remaining elements of the ALD 100 may be found in U.S. Patent
Application Publication Nos. US 2009/0062970 A1 and US 2009/0063228
A1, wherein the ALD 100 is also described in the context of an
individual server embodiment.
[0052] In one embodiment, a sampling repository is used to
facilitate the determination of dispatchable operating reserve
power or energy (e.g., spinning and/or regulating reserve) for a
utility. An exemplary sampling repository 500 is shown in block
diagram form in FIG. 5. As illustrated in FIG. 5, the sampling
repository 500 is a means for storing device monitoring data and
other data that collectively details how devices (e.g., a hot water
heater 40 as shown in FIG. 5) have behaved under specific
conditions. The repository 500 may be in various forms, including a
matrix, a database, etc. In one embodiment, the sampling repository
500 is implemented in the ALD database 124 of the ALD 100.
Alternatively, the sampling repository 500 may reside elsewhere
within the ALD 100 or be external to the ALD 100. The sampling
repository 500 contains all power consumption data for devices
located at a device or service point 20 or within a utility. Power
consumption data may include, but is not limited to: current
reading, energy/power used or consumed, energy/power saved, drift
or drift rate, power time, user settings for maximum environmental
variances, time periods (e.g., hours of the day, days of the week,
and calendar days). Taken collectively, this data is used to show
how devices behaved during normal operation as well as during
control events in which power is temporarily interrupted or reduced
to one or more devices. The data may be obtained via passive
sampling (e.g., regular monitoring of devices at a particular
service point 20 by the active load client 300 associated with the
service point 20) and/or active sampling (e.g., direct polling of
the devices for the data by the active load client 300 or the ALD
100). As discussed below, the sampling repository 500 is used by
the ALD 100 or other components of the ALMS 10 to estimate or
project power consumption behavior of the devices and to determine
projected power/energy savings resulting from a control event. The
projected power savings may be determined using the power savings
application 120 based upon the power consumption data in the
repository 500.
[0053] FIG. 6 is an exemplary screen shot displayed to a user
(e.g., customer) during execution of a customer personal settings
application 138. The illustrated screen shot shows a screen being
used to set the customer preferences for an
environmentally-dependent device, such as an HVAC unit 50, a
humidifier, or a pool heater. The illustrated screen shot may be
provided to the customer in one embodiment via an
Internet-accessible web portal 98 (referred to herein as the
"customer dashboard") when such portal is accessed by the customer
via a computer, smart phone, or other comparable device. As shown
in FIG. 3, the customer dashboard 98 may be connected to the ALD
100 via an Internet service provider for the service point 20 or
may be implemented as a customer Internet application 92 when
Internet service is supplied through the active load client 300 as
described in U.S. Patent Application Publication No. US
2009/0063228 A1. The customer dashboard 98 effectively provides the
customer with access into the ALD 100. The ALD's web browser
interface 114 accepts inputs from the customer dashboard 98 and
outputs information to the customer dashboard 98 for display to the
customer. The customer dashboard 98 may be accessed from the
service point 20 or remotely from any Internet-accessible device,
preferably through use of a user name and password. Thus, the
customer dashboard 98 is preferably a secure, web-based interface
used by customers to specify preferences associated with devices
controlled by the ALD 100 and located at the customer's service
point 20, as well as to provide information requested by the
customer personal settings application 138 or the customer sign-up
application 116 in connection with controlled devices and/or
service point conditions or parameters. Customer preferences may
include, for example, control event preferences (e.g., times,
durations, etc.), bill management preferences (e.g., goal or target
for maximum monthly billing cost), maximum and minimum boundary
settings for environmental characteristics, and others.
[0054] FIG. 7 is another exemplary screen shot displayed to a
customer via the customer dashboard 98 during execution of a
different portion of the customer personal settings application
138. FIG. 7 shows how customer preferences could be set for an
environmentally-independent device, such as a hot water heater 40,
a pool pump 70, or a sprinkler system water pump (which may also be
an environmentally-dependent device if it includes, for example, a
rainfall sensor). Using the web browser interface 114, customers
interact with the ALD 100 and specify customer personal settings
138 that are recorded by the ALD 100 and stored in the ALD database
124 or other repository 500. The personal settings 138 may specify
time periods during which load control events are permitted, time
periods during which load control events are prohibited, maximum
allowable variances for an operating environment at a particular
service point 20 (e.g., maximum and minimum temperature and/or
humidity), normal operating conditions of devices at different
times of day, and other personal preferences related to operation
of devices under the control of the ALD 100 through the active load
client 300 at the service point 20.
[0055] As alluded to above, the present invention optionally tracks
and takes into account the "drift" of an environmentally-dependent
device. Drift occurs when the environmental characteristic(s)
(e.g., temperature) monitored by an environmentally-dependent
device begins to deviate (e.g., heat up or cool down) from a set
point that is to be maintained by the environmentally-dependent
device. Such deviation or drift may occur both normally and during
control events. Thus, drift is the time it takes for the monitored
environmental characteristic to move from a set point to an upper
or lower comfort boundary when power, or at least substantial
power, is not being consumed by the device. In other words, drift
is a rate of change of the monitored environmental characteristic
from a set point without use of significant power (e.g., without
powering an HVAC unit compressor, but while continuing to power an
associated digital thermostat and HVAC unit control system). One of
ordinary skill in the art will readily appreciate that devices,
such as HVAC units 50, which control one or more environmental
characteristics at a service point 20, are also influenced or
affected by the environment at the service point 20 because their
activation or deactivation is based on one or more sensed
environmental characteristics at the service point 20. For example,
an HVAC unit 50 in cooling mode that attempts to maintain an inside
temperature of 77.degree. F. activates when the inside temperature
is some temperature greater than 77.degree. F. and, therefore, is
influenced or affected by the environment in which the HVAC unit 50
operates.
[0056] The inverse of drift is "power time," which is the time it
takes for the sensed environmental characteristic to move from a
comfort boundary to a set point when significant or substantial
power is being supplied to the environmentally-dependent device. In
other words, "power time" is a rate of change of the monitored
environmental characteristic from a comfort boundary to a set point
with significant use of power. Alternatively, "drift" may be
considered the time required for the monitored environmental
characteristic to move to an unacceptable level after power is
generally turned off to an environmentally-dependent device. By
contrast, "power time" is the time required for the monitored
environmental characteristic to move from an unacceptable level to
a target level after power has been generally supplied or
re-supplied to the environmentally-dependent device.
[0057] The power consumption data for an environmentally-dependent
device, which may be gathered actively or passively as described
above, may be used to empirically determine the drift and power
time (rate of change, temperature slope, or other dynamic equation
(f{x})) that defines an environmental characteristic's variation at
a service point 20, or at least within the operating area of the
environmentally-dependent device, so as to permit the determination
of a uniquely derived "fingerprint" or power usage/consumption
pattern or behavior for the service point 20 or the
environmentally-dependent device.
[0058] Customers define the upper and lower boundaries of comfort
by inputting customer preferences 138 through the web browser
interface 114, with the set point optionally being in the middle of
those boundaries. During normal operation, an
environmentally-dependent device will attempt to keep the
applicable environmental characteristic or characteristics near the
device's set point or set points. However, all devices, whether
environmentally-dependent or environmentally-independent, have a
duty cycle that specifies when the device is in operation because
many devices are not continuously in operation. For an
environmentally-dependent device, the duty cycle ends when the
environmental characteristic(s) being controlled reaches the set
point (or within a given tolerance or variance of the set point).
After the set point has been reached, the environmentally-dependent
device is generally turned off and the environmental characteristic
is allowed to "drift" (e.g., upward or downward) toward a comfort
boundary. Once the environmental characteristic (e.g., temperature)
reaches the boundary, the environmentally-dependent device is
generally activated or powered on again until the environmental
characteristic reaches the set point, which ends the duty cycle and
the power time.
[0059] Drift may also occur during a control event. A control event
is an action that temporarily reduces, terminates, or otherwise
interrupts the supply of power to a device. During a control event,
the environmental characteristic (e.g., temperature) monitored
and/or controlled by an environmentally-dependent device will drift
toward a comfort boundary (e.g., upper or lower) until the
environmental characteristic reaches that boundary. Once the
environmental characteristic reaches the boundary, the ALMS 10
generally returns or increases power to the device to enable the
environmental characteristic to reach the set point again.
[0060] For example, an HVAC unit 50 may have a set point of
72.degree. F. and minimum and maximum comfort boundary temperatures
of 68.degree. F. and 76.degree. F., respectively. On a cold day, a
control event may interrupt power to the HVAC unit 50 causing the
monitored temperature within the service point 20 to move toward
the minimum comfort boundary temperature. Once the monitored
temperature inside the service point 20 reaches the minimum comfort
boundary temperature, the control event would end, and power would
be restored or increased to the HVAC unit 50, thus causing the
monitored temperature to rise toward the set point. A similar, but
opposite effect, may take place on a warm day. In this example,
"drift" is the rate of change with respect to the time it takes the
HVAC unit 50 to move from the set point to either the upper or
lower comfort bounds. Analogously, "power time" is the rate of
change with respect to the time required for the HVAC unit 50 to
move the monitored temperature from the upper or lower comfort
bounds to the set point. In one embodiment of the present
invention, drift and power time are calculated and recorded for
each environmentally-dependent or environmentally-independent
device or for each service point 20.
[0061] In another embodiment, drift and other measurement data
available from the ALD database 124 are used to create a power
consumption behavior or pattern for each environmentally-dependent
or environmentally-independent device or for each service point 20.
The other measurement data may include vacancy times, sleep times,
times in which control events are permitted, and/or other
variability factors.
[0062] The environment within an energy-efficient structure will
have a tendency to exhibit a lower rate of drift. Therefore,
environmentally-dependent devices operating within such structures
may be subject to control events for longer periods of time because
the amount of time taken for the monitored environmental
characteristic to reach a comfort boundary due to drift after being
set to a set point is longer than for less efficient
structures.
[0063] In another embodiment, the ALD 100 may identify service
points 20 that have an optimum drift for power savings. The power
savings application 120 calculates drift for each service point 20
and/or for each environmentally-dependent device at the service
point 20, and saves the drift information in the ALD database 124
as part of power consumption data for the device and/or the service
point 20. Thus, power saved as a result of drift during a control
event increases overall power saved by the
environmentally-dependent device at the service point 20.
[0064] FIG. 8 illustrates an exemplary operational flow diagram 800
providing steps executed by the ALD 100 to empirically analyze
power usage of devices and populate a repository 500 with data
samples resulting from such power usage analysis, in accordance
with one embodiment of the present invention. The steps in FIG. 8
may be considered to implement a passive sampling algorithm. The
steps of FIG. 8 are preferably implemented as a set of computer
instructions (software) stored in memory (not shown) of the ALD 100
and executed by one or more processors 160 of the ALD 100.
[0065] According to the logic flow, the active load client 300
polls devices within the service point 20, such as a washer/dryer
30, hot water heater 40, HVAC unit 50, smart appliance 60, pool
pump 70, or other devices within the service point 20, and obtains
current readings. Upon receiving the current reading data from the
active load client 300, the ALC interface 112 sends the data to the
ALC manager 108. The ALC manager 108 stores the data to the
sampling repository 500, which may be implemented in the ALD
database 124 using the operational flow illustrated in FIG. 8.
[0066] The following information may be provided as parameters to
the operational flow of FIG. 8: an identification (ID) of the
device, temperature mode (either "heating" or "cooling"), duty
cycle, current temperature read by the device, and previous
temperature read by the device. Each temperature reading includes a
device ID, a set point (which is only useful for
environmentally-dependent devices), and variability factor
measurement data (as described previously).
[0067] Initially, the ALD 100 determines (802) whether the device
used any, or at least any appreciable amount of, energy. If not,
then the logic flow ends. Otherwise, the ALD 100 determines (804)
the time duration of the data sample, the time duration when the
device was on, and the time duration when the device was off based
on the data sample. Next, the ALD 100 determines (806) whether the
received data comes from an environmentally-dependent device or an
environmentally-independent (e.g., binary state) device. If the
received data comes from an environmentally-dependent device, then
the ALD 100 determines (808) the energy used per minute for the
device, and determines (810) whether the device is drifting or
powering. The ALD 100 determines that the device is drifting if the
environmental characteristic monitored by the device is changing in
a manner opposite the mode of the device (e.g., the room
temperature is rising when the device is set in cooling mode or the
room temperature is decreasing when the device is set in heating
mode). Otherwise, the device is not drifting.
[0068] If the device is drifting, then the ALD 100 determines (814)
the drift rate (e.g., degrees per minute). On the other hand, if
the device is not drifting, then the ALD 100 determines (812) the
power time rate. Once either the drift rate or the power time rate
has been calculated, the ALD 100 determines (880) whether there is
already a record in the sampling repository 500 for the device
being measured under the present operating conditions of the device
(e.g., set point and other variability factors (e.g., outside
temperature)). If there is no existing record, then the ALD 100
creates (882) a new record using, for example, the device's ID,
time of record, current set point, current outside temperature,
energy used per minute, power time rate, and drift rate (assuming
that either a power time rate or a drift rate has been determined).
However, if there is an existing record, then the ALD 100 updates
(884) the existing record by averaging the new data (including
energy usage, drift rate, and power time rate) with the existing
data and storing the result in the repository 500.
[0069] If the ALD 100 determines (806) that the received data comes
from an environmentally-independent device, then the ALD 100
determines (842) the energy used per minute for the device and
further determines (844) the energy saved per minute for the
device. The ALD 100 then searches the repository 500 (e.g., ALD
database (124)) to determine (890) whether there is already a
record for the device for the applicable time period. If there is
no existing record, then the ALD 100 creates (892) a new record
using the device's ID, time of record, current time block, energy
used per minute, and energy saved per minute. However, if there is
an existing record, then the ALD 100 updates (894) the existing
record by averaging the new data (including energy usage and energy
savings) for the time block with the existing data for the time
block and stores the result in the repository 500. For
environmentally-independent devices, energy usage and energy
savings are saved with respect to a block or period of time.
[0070] FIG. 9 illustrates an exemplary operational flow diagram 900
providing steps executed by the ALD 100 to project or estimate the
energy usage expected of a device during a future time period in a
given environment setting, in accordance with one embodiment of the
present invention. The steps of FIG. 9 are preferably implemented
as a set of computer instructions (software) stored in memory (not
shown) of the ALD 100 and executed by one or more processors 160 of
the ALD 100. In accordance with one embodiment, the operational
flow of FIG. 9 may be executed by the power savings application 120
of the ALD 100 when a utility operator, or other operator of the
ALD 100, wants to project the energy usage for a device over a
specified time period in the future, such as during a period of
time in which a control event is to occur.
[0071] The following information may be provided as parameters to
the operational flow of FIG. 9: the device ID, the start time of
the future time period, the end time of the future time period, the
manage mode of the device, and, for an environmentally-independent
device, a binary control factor. The manage mode is either
"control" or "normal" to indicate whether the device is being
measured during a control event or during normal operation,
respectively. The binary control factor is preferably utilized for
environmentally-independent devices and represents the duty cycle
of the device. For example, if a water heater 40 runs at 20% duty
cycle, the binary control factor is 0.2.
[0072] Initially, the ALD 100 (e.g., power savings application 120)
determines (902) a future time period based on the start and stop
times. The future time period may be set by the utility
implementing the load control procedure of the present invention or
a second utility that has requested delivery of operating reserve
power from the utility implementing the load control procedure of
the present invention. After the time period at issue is known, the
power savings application 120 begins the procedure for projecting
or estimating the amount of power that can be saved as the result
of execution of a control event during the future time period.
Accordingly, the power savings application 120 analyzes the devices
to be controlled during the control event. Thus, the power savings
application 120 determines (904) whether the devices include both
environmentally-dependent and environmentally-independent (e.g.,
binary state) devices. For each environmentally-dependent device,
the power savings application 120 determines (920) whether the
device is in environment controlling (e.g., heating or cooling)
mode. Next, the power savings application 120 retrieves (922) the
anticipated set points for the device during the future time period
of the control event and obtains (924) information regarding the
outside environmental characteristic(s) (e.g., the outside
temperatures) expected during the control event time period. The
power savings application 120 then makes projections (926) about
the device's expected power consumption behavior during the future
time period. In one embodiment, the projection determination of
block 926 is implemented using a best match algorithm, as described
in detail below with respect to FIG. 10, to find stored repository
records that best match the behavior of the device for each
combination of set points, outside environmental characteristics
(e.g., temperatures), and time periods, as measured and stored
using the logic flow of FIG. 8. The power consumption behavior of
the device is used to determine the amount of energy that would be
expected to be used by the device if the control event did not
occur and, thus, the amount of energy estimated or expected to be
saved per unit time during the control event. The power savings
application 120 multiplies (928) the saved power per unit time by
the time duration of the future control event to determine the
total amount of energy projected to be used by the device in the
absence of the control event. The power savings application returns
(980) the total projected amount of energy used by the device in
the absence of the proposed control event.
[0073] However, if the power savings application 120 determines
(904) that the proposed control event is to affect an
environmentally-independent device, then the power savings
application 120 determines (960) whether the device is currently
scheduled to be on or off during the proposed time period of the
control event. Next, the power savings application 120 creates,
obtains, or otherwise determines (962) a list of time blocks for
the specified control event time period. The power savings
application 120 then makes projections (964) about the device's
power consumption behavior during the future, control event time
period. In one embodiment, the projection determination of block
964 is implemented using a best match algorithm, as described in
detail below with respect to FIG. 10, to find stored repository
records that best match the behavior of the device for each
combination of set points, outside environmental characteristics
(e.g., temperatures), and time periods, as measured and stored
using the logic flow of FIG. 8. The power consumption behavior of
the device is used to determine the amount of energy that would be
expected to be used by the device if the control event did not
occur and, thus, the amount of energy estimated or expected to be
saved per unit time during the control event. Next, the power
savings application 120 multiplies (968) the saved power per unit
time by the time duration of the future control event to determine
the total amount of energy projected to be used in the absence of
the control event. If the projected energy savings is based on
power consumption during a previous control event (970), then the
power savings application 120 multiplies (972) the total amount of
energy times the binary control factor to determine the amount of
energy projected to be used by the device in the absence of the
control event. The power savings application returns (980) the
total projected amount of energy used by the device in the absence
of the proposed control event.
[0074] One or ordinary skill in the art will readily recognize and
appreciate that the operational flow of FIG. 9 may be used for each
controlled device at a service point, for the controlled devices at
multiple service points, or for all the controlled devices at all
the service points supplied or supported by a utility. The total
projected energy usage by the devices may be aggregated across a
single service point, for all service points within a group, and/or
for all groups served by the utility.
[0075] FIG. 10 illustrates an exemplary operational flow diagram
1000 providing steps executed by the ALD 100 for estimating power
consumption behavior of a device in accordance with an exemplary
embodiment of the present invention. The algorithm or operational
flow illustrated in FIG. 10 provides one embodiment for
implementing steps 926 and 964 of FIG. 9. The operational flow of
FIG. 10 determines which record or records in the sampling
repository 500 provides the closest match to a given environment or
operational setting for use in projecting device energy
usage/savings during a time period of a future control event, in
accordance with one embodiment of the present invention. The steps
of FIG. 10 are preferably implemented as a set of computer
instructions (software) stored in memory (not shown) of the ALD 100
and executed by one or more processors 160 of the ALD 100. The
operational flow of FIG. 10 may be initiated by the ALD 100 when
trying to identify or determine the sampling repository record or
records that best match the power consumption behavior of a device
in a specific setting.
[0076] In one embodiment, the operational flow of FIG. 10 is called
during execution of the operational flow of FIG. 9 as noted above.
When so called, the operational flow of FIG. 9 provides the
operational flow of FIG. 10 with parameters that indicate the type
of records to be searched. These parameters include, but are not
limited to: a device ID, a duty mode (either on or off), a time
period (e.g., corresponding to the time period of the proposed
future control event), a set point delta, a delta or variance
related to one or more environmental characteristics (e.g., outside
temperature), and a time block delta. Duty mode signifies the duty
cycle of the device. If the duty mode is TRUE or ON, significant
power is being consumed. If the duty mode is FALSE or OFF,
significant power is not being consumed (i.e., power is being
saved). Duty cycle exists for switch-controlled, binary state, or
environmentally-independent devices which go ON and OFF
irrespective of the influence or affect of environment. For HVAC
devices 50, duty mode is always ON. Set point delta is the amount a
set point may be varied during a search in order to find a matching
repository record. Outside temperature/environmental characteristic
delta is the number of temperature degrees or other change in
environmental characteristics over which data relating to the
outside temperature or other environmental characteristics may be
varied during a search in order to find a matching repository
record. Time block delta is the amount of time a time block may be
varied during a search in order to find a matching repository
record.
[0077] Initially, the ALD 100 determines (1002) whether the
requested repository search relates to an environmentally-dependent
device or an environmentally-independent device. If the search
relates to an environmentally-dependent device, then the ALD 100
attempts to find (1004) power consumption records in the sampling
repository 500 that match the device ID, duty mode, environmental
characteristic (e.g., temperature) set point, and associated
outside environmental characteristic data. Power consumption
records include power consumption data, such as power consumed,
current drawn, duty cycle, operating voltage, operating impedance,
time period of use, set points, ambient and outside temperatures
during use (as applicable), and/or various other energy use data.
If a record exists that matches all the power consumption search
criteria, such record would be considered the record that most
closely matches the given environment setting. If no exact match is
found (1010), then the ALD 100 begins looking for records that
slightly differ from the given environment setting. In one
embodiment, the ALD 100 incrementally increases or decreases (1012)
the environment-related search criteria (e.g., temperature set
point and/or outside/ambient temperature) using the set point delta
and the outside temperature/environmental characteristic delta as a
guide to look for relevant records. Such incremental/iterative
modification of the search criteria continues until either relevant
records are found or some applicable limit (e.g., as indicated by
the set point delta and/or other parameter deltas) is reached.
[0078] If the ALD 100 determines (1002) that the search relates to
an environmentally-independent device, then the ALD 100 attempts to
find (1040) power consumption records in the sampling repository
500 that match the device ID, duty mode, and time of operation
(corresponding to the expected, future time of the control event).
If a record is not found that matches all the search criteria
(1070), then the ALD 100 modifies its search to look for records
that slightly differ from the given environment setting. In one
embodiment, the ALD 100 modifies its search by incrementally
increasing or decreasing (1072) the time of operation for a given
duty mode. The iterative searching continues until either relevant
records are found or some applicable limit (e.g., as indicated by
the time block delta or other parameter deltas) is reached. Any
records that were found as a result of the search are provided
(1060) to the requesting program (e.g., the operational flow of
FIG. 9). The result of the operational flow of FIG. 10 is a set of
one or more power consumption records from the sampling repository
500 that are the closest match to the given environment or proposed
control event setting.
[0079] FIG. 11 illustrates an exemplary operational flow diagram
1100 providing steps executed by the ALD 100 to project energy
savings through power interruption or reduction to a device during
a control event, in accordance with one embodiment of the present
invention. The steps of FIG. 11 are preferably implemented as a set
of computer instructions (software) stored in memory (not shown) of
the ALD 100 and executed by one or more processors 160 of the ALD
100. As with the operational flow of FIG. 9, the operational flow
of FIG. 11 may be executed by the power savings application 120
when an operator of the utility or of the ALD 100 wants to project
the energy savings for a device over a specified time period during
operation of a control event.
[0080] The following information may be provided as parameters to
the operational flow of FIG. 11: a device ID, a start time of the
control event, an end time of the control event, and a binary
control factor, as described above in connection with FIG. 9.
Initially, the ALD 100 (e.g., power savings application 120)
projects (1102) the energy usage/power consumption for the device
during normal operation within the expected time period of the
control event using, for example, the operational flow of FIG. 9.
Next, the power savings application 120 projects (1104) the power
consumption for the device during the control event using, for
example, the operational flow of FIG. 9. For example, depending on
the duty cycle, set points, drift or drift rate, power time, and
other parameters for the device, the device may be projected to be
on and consuming power for some amount of time during the time
period of the control event. Thus, both the expected amount of
power consumed during normal operation (i.e., in the absence of any
control event) and the expected amount of power consumed during the
control event are determined to accurately assess any possible
power savings as a result of the control event. After the two
projected power consumption values have been determined, the power
savings application 120 calculates (1106) the difference between
the two values, which is the projected power consumption for the
device during the control event time period. Because the projected
power consumption will not be realized during the control event,
such power consumption corresponds directly to an amount of energy
saved during the control event. The power savings application 120
returns (1108) the projected energy savings value. One of ordinary
skill in the art will readily recognize and appreciate that the
power savings application 120 may aggregate the projected power
savings for all controlled devices at a service point 20, for all
controlled devices at service points within a group, or for
controlled devices within all service point groups served by the
utility to obtain an aggregate amount of power savings as a result
of a control event.
[0081] Another context in which the ALMS 10 may be utilized is in
conjunction with other renewable energy sources. A number of
renewable energy sources, such as wind power and solar power, are
variable in nature. That is, such energy sources do not generate
power at a constant rate. For example, wind increases or decreases
from moment to moment. Wind turbines can generate a large amount of
power due to large winds or can stop generating completely due to
lack of any wind. Solar panels may be able to generate a great deal
of power on very sunny days, a little power on cloudy days, and
virtually no power at night.
[0082] As a result, power utilities that make use of renewable
energy must compensate for the under-generation or over-generation
of power from those sources. When renewable energy sources are
under-generating, the ALMS 10 may utilize the processes disclosed
above to provide additional operating reserve to compensate for the
lack of power generation by the renewable energy source and for the
effects resulting therefrom, including output frequency
instability. For example, a utility utilizing wind or solar energy
sources may further incorporate the ALMS 10 into the utility
distribution system to provide regulating reserve during time
periods of under-generation.
[0083] FIG. 12 is a graph that depicts the "load profile" of a
utility over a predetermined time period, showing actual energy
usage as well as projected energy usage determined with and without
a control event in accordance with an exemplary embodiment of the
present invention. The load profile graph depicts the following:
[0084] a. Baseline power consumption 1202. This is the total
possible load of, or power consumed by, all controlled devices over
a specified period of time. [0085] b. Projected interruptible load
usage 1204 (i.e., projected load or energy usage with a control
event) for all controlled devices at all service points (or at
selected service points) served by the utility in the absence of a
control event. The projected interruptible load usage may be
determined in one embodiment through execution of the operational
flow of FIG. 9. The projected interruptible load available 1204
indicates the load for all controlled devices if they are
controlled 100% of the time using customer preferences. [0086] c.
Projected interruptible load available 1206 (i.e., projected energy
used when no control events are used) for all controlled devices at
all service points (or at selected service points) served by the
utility during a control event. The projected interruptible load
usage may be determined in one embodiment through execution of the
operational flow of FIG. 11. [0087] d. Actual interruptible load
usage 1208 for all controlled devices at all service points (or at
selected service points) served by the utility. The actual
interruptible load usage 1208 is the power that is currently being
used by all controlled devices. This type of load profile graph may
be generated for all controlled devices at a service point 20, for
controlled devices at all service points within a group, or for
controlled devices at all groups served by the utility.
[0088] In the load profile graph of FIG. 12, the capacity under
contract is shown as a straight double line at the top of the graph
and indicates the baseline power consumption 1202. The baseline
power consumption 1202 represents the total amount of power that
the utility is obligated to provide. The actual interruptible load
usage 1208 is the actual energy usage of all devices controlled by
the utility. The projected interruptible load usage 1204 at the
bottom of the load profile graph is the projected energy used when
control events are used, and the projected interruptible load
available 1206 is the projected energy usage when control events
are not used. The difference between the projected interruptible
load usage 1204 and the projected interruptible load available 1206
is the capacity that may be used for operating reserve, including
regulating reserve, spinning reserve, and non-spinning reserve.
[0089] Normally, when a utility observes energy demand that is near
its peak capacity, it will attempt to initiate control events for
customers who voluntarily participate in power saving programs
(i.e., flexible load-shape programs, as described earlier).
Typically, these control events will provide sufficient capacity to
prevent the utility from using non-spinning reserve. However, there
are situations in which a sufficient number of customers may have
manually decided to opt out of power saving programs and, as a
result, the utility would be unable to recover enough energy to
meet its spinning reserve needs from its remaining customers who
voluntarily participate in the program. Such a situation could
happen, for instance, on a very hot day when many people are home,
such as on a holiday or a day over the weekend. In such a case, the
utility would still be in danger of using non-spinning reserve or
even running out of reserve capacity altogether. In such a
situation, the utility would be in a "critical control" mode. In
critical control mode, the utility may override all customer
preferences, including both those who voluntarily participate in
power saving programs and those who do not. During periods of
critical control, the utility may utilize the ALD 100 to adjust
settings of environmentally-dependent devices to settings outside
of normal comfort preferences (but not life-threatening). Invoking
critical control enables a utility to return power demand to
acceptable levels.
[0090] Use of the ALMS 10 may help a utility mitigate the
likelihood of critical control situations. For example, whenever a
customer overrides or opts out of a control event, the ALMS 10,
using the techniques disclosed herein, finds additional customers
who may be the target of a voluntary control event. Analogously,
when controlled devices that are participating in a control event
are required to exit the control event due to customer preferences
(e.g., the amount of time that the customer's devices may
participate in a control event), the ALD 100 may release such
devices from the control event and replace them with other
voluntarily controlled devices. The replacement devices would then
preferably supply, through deferment, at least the same amount of
reserve power as was being sourced by the devices that were
released from the control event. Thus, the system 10 of the present
invention increases the likelihood that a utility will be able to
spread control events to other customers before invoking critical
control.
[0091] In a further embodiment, the entire ALMS 10 described in
FIG. 3 may also be implemented in a proprietary network that is
IP-based, real-time, temperature-derived, verifiable, interactive,
two-way, and responsive to Automatic Generation Control (AGC)
commands to produce operating reserve power through implementation
of control events.
[0092] In an additional embodiment of the present invention, the
sampling data stored in the repository 500 using the operational
flow of FIG. 5 could also include other factors (called
"variability factors") related to power consumption, such as day of
the week, humidity, amount of sunshine, or number of people in the
household. This additional data would allow the projected energy
usage and projected energy savings to be more accurate based on
these additional factors. To make use of this data, the ALD 100 may
obtain the additional data from sources within and/or external to
the ALMS 10, such as weather databases, live weather feeds from
sources such as National Weather Reporting stations, outdoor
sensors 94, or any weather related input device commercially
available on a real time or predictive basis, calendars, and
voluntary customer feedback. Some of the variability factor
measurements are available from public sources, while others are
available via private sources.
[0093] In another alternative embodiment of the present invention,
transmission line loss may be included in the projected energy
savings determination of FIG. 11. As those of ordinary skill in the
art will recognize and appreciate, the amount of power supplied by
a utility to source a device remote from the utility equals the
amount of power required by the device plus the amount of power
lost in the transmission lines between the utility's power
generation plant and the location of the device. Thus, the
projected energy savings resulting from a control event may be
determined by determining an amount of power expected to be
consumed by the controlled device or devices at a service point, at
multiple service points or throughout the entire service area of
the utility during the time period of the control event absent
occurrence of the control event to produce first energy savings,
determining an amount of power that is not expected to be
dissipated in transmission lines as a result of not delivering
power to the controlled device or devices during the control event
to produce second energy savings, and summing the first energy
savings and the second energy savings.
[0094] In a further embodiment of the present invention, the
operating reserve (e.g., spinning reserve or regulating reserve)
determined by a utility using the techniques disclosed above can be
sold to a requesting utility 1306, as illustrated in FIG. 13, which
is essentially a replication of FIG. 9 of U.S. Patent Application
Publication No. US 2009/0063228 A1. As explained in U.S. Patent
Application Publication No. US 2009/0063228 A1, the saved power may
then be distributed to the requesting utility 1306 after
commencement of the control event (e.g., during and/or after
completion of the control event) conducted by the selling utility.
The selling utility may be a virtual utility 1302 or a serving
utility 1304 as illustrated in FIG. 13 and described in detail in
U.S. Patent Application Publication No. US 2009/0063228 A1.
Alternatively, a third party may serve as a managing entity to
manage operation of the ALMS 10 and the resultant distribution of
operating reserve to a requesting utility 1306 subsequent to
commencement of a control event.
[0095] In yet another embodiment, the ALD 100 for a utility may
determine projected energy savings for each service point 20 served
by the utility in accordance with the operational flow of FIG. 11
and aggregate the projected energy savings across all service
points served by the utility to obtain the total projected energy
savings from which operating reserve may be determined as described
above.
[0096] In a further embodiment, instead of or in addition to using
the operational flow of FIG. 10 in an attempt to find a best match
data point in the repository 500 for use in estimating power
consumption behavior of a device when the time period of the
control event does not correspond to a time period in the
repository 500, the ALD 100 may determine whether the repository
500 includes power consumption data for the device during time
periods before and after the expected time period of the control
event and, if so, interpolate a value corresponding to an amount of
power expected to be consumed by the device during the time period
of the control event based on the power consumption data for the
device during the time periods before and after the expected time
period of the control event.
[0097] In yet another embodiment, a requesting utility may utilize
a method for acquiring operating reserve power from a sourcing
utility. According to this embodiment, the requesting utility
requests operating reserve power from the sourcing utility
sufficiently in advance of a transfer time at which the operating
reserve power will be needed so as to facilitate measurable and
verifiable load-controlled generation of the operating reserve
power. The load-controlled generation of the operating reserve
power results from a determination of operating reserve as detailed
above with respect to FIGS. 7-12. The requesting utility receives
an acknowledgment from the sourcing utility indicating that the
sourcing utility will supply the operating reserve power at the
transfer time. Then, at the transfer time and for a time period
thereafter, the requesting utility receives at least some of the
operating reserve power from the sourcing utility.
[0098] In a further embodiment, the operating reserve determination
techniques may be utilized by a virtual utility 1302 as disclosed
in U.S. Patent Application Publication No. US 2009/0063228 A1. For
example, the virtual utility 1302 may be operable to at least offer
energy to one or more requesting utilities 1306 for use as
operating reserve for the requesting utilities 1306. In such a
case, the virtual utility 1302 may include, among other things, a
repository 500 and a processor 160 (e.g., within an ALD 100). In
this embodiment, the processor 160 is operable to remotely
determine, during at least one period of time, power consumed by at
least one device to produce power consumption data. The processor
160 is further operable to store the power consumption data in the
repository 500 and, at the appropriate time, determine an expected,
future time period for a control event during which power is to be
reduced to the device or devices. The processor 160 is also
operable to estimate, prior to commencement of the control event,
power consumption behavior expected of the device or devices during
the time period of the control event based at least on the stored
power consumption data. The processor 160 is further operable to
determine, prior to commencement of the control event, projected
energy savings resulting from the control event based at least on
the estimated power consumption behavior of the device or devices.
Still further, the processor 160 is operable to determine, prior to
commencement of the control event, operating reserve based on the
projected energy savings. After determination of the operating
reserve, the processor 160 is operable to communicate an offer to
supply the operating reserve to a requesting utility 1306 or
utilities.
[0099] As described above, the present invention encompasses a
system and method for determining operating reserve capacity using
an ALD or comparable device, software, or combination thereof so
that the operating reserve capacity may be made available to the
power utility that generated the operating reserve through load
control or to the power market generally (e.g., via the FERC grid).
When a utility requires power beyond its native load, the utility
must make use of its operating reserve or acquire the additional
power via the FERC grid from other utilities. As discussed above,
one type of operating reserve is spinning reserve. Spinning reserve
is additional generating capacity that is already connected to the
power system and, thus, is almost immediately available. In
accordance with one embodiment of the present invention, the ALD
makes spinning reserve available to a utility. Thus, through use of
the ALD, a utility (power generating utility or a virtual utility)
can determine or project spinning reserve or other operating
reserve that is available through interruptible power savings at
service points. The spinning reserve is measurable and verifiable,
and can be projected for a number of days in advance, and such
projections can be sold to other utilities on the open market.
[0100] As disclosed above, the ALD 100 may be considered to
implement a type of flexible load-shape program. However, in
contrast to conventional load control programs, the load-shape
program implemented by the ALD 100 projects an amount of operating
reserve resulting from selective control of devices (loads) based
on known, real-time customer preferences. In addition, due to its
communication and control mechanisms, the ALD 100 can project power
savings, as well as operating reserve (e.g., regulating, spinning
and/or non-spinning reserve) that is active, real-time, verifiable,
and measurable so as to comply with protocols and treaties
established for the determination of carbon credits and offsets, as
well as renewable energy credits. The information acquired by the
ALD 100 is not simply samples of customer preferences and data, but
actual power consumption information.
[0101] In the foregoing specification, the present invention has
been described with reference to specific embodiments. However, one
of ordinary skill in the art will appreciate that various
modifications and changes may be made without departing from the
spirit and scope of the present invention as set forth in the
appended exemplary claims. For example, the passive sampling
algorithm of FIG. 8, the projected energy usage algorithm of FIG.
9, the best sampling match algorithm of FIG. 10, and the projected
energy savings algorithm of FIG. 11 may be performed by one or more
equivalent means. Accordingly, the specification and drawings are
to be regarded in an illustrative rather than a restrictive sense,
and all such modifications are intended to be included within the
scope of the present invention.
[0102] Benefits, other advantages, and solutions to problems have
been described above with regard to specific embodiments of the
present invention. However, the benefits, advantages, solutions to
problems, and any element(s) that may cause or result in such
benefits, advantages, or solutions to become more pronounced are
not to be construed as a critical, required, or essential feature
or element of any or all the claims. The invention is defined
solely by the appended claims including any amendments made during
the pendency of this application and all equivalents of those
claims as issued.
* * * * *